Host population effects on ectomycorrhizal fungi
Bibliographic record
Abstract
Geographic distinctions in the affinity of tree populations for select ectomycorrhizal fungi (EMF) may occur where strong edaphic pressures act on fungal communities and their hosts. We examine this premise for Pseudotsuga menziesii var. menziesii of southwest British Columbia, using ten native seedlots collected from a range of mean annual precipitation (MAP), as a proxy for podzolization extent and phosphorus (P) deficiencies, and evaluated in contrasting low P and high P soils. After two growing seasons, seedling biomass in the high P soil dwarfed that of the low P soil, and better growth rates under high P were detected for populations from very dry and very wet origins. EMF communities on the high P soil displayed more symmetry among host populations than the low P soil (average community dissimilarity of 0.20% vs 0.39%, respectively). Seedling foliar P% differed slightly but significantly in relation to MAP of origin. EMF species richness varied significantly among host populations but independently of climatic parameters. There were significant shifts in EMF species abundance related to seedlot MAP, particularly on the low P soil where nonlinear relationships were found for Wilcoxina mikolae, Hyaloscypha finlandica, and Rhizopogon villosulus. Despite efforts to enhance colonization by native fungi, the predominance of ruderal EMF species hindered a realistic evaluation of local adaptation among host-fungi populations. Nevertheless, the shifting affinity in taxa abundance and wider community disparity on low P soil reflected the potential for a consequential host genetic effect related to geographical patterns in P availability across temperate rainforests
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".